In Silico Optimization of Lipid Production in Rhodosporidium Toruloides by Gene Knockout Strategies

María Teresita Castañeda1, Sebastián Nuñez1, Claudio Voget1, Hernán De Battista1

  • 1Universidad Nacional de La Plata - CONICET



Regular Session


10:00 - 11:40 | Wed 24 Apr | Baia Norte | WeA3

Metabolic Network Analysis

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Microbial lipids are being extensively studied as an alternative to vegetable oils in biodiesel production. For the biotechnological production of biolipids, efficient processes capable of obtaining significant biomass productivity with high lipid titer are required. In this work, we used the Optknock algorithm for the assessment of non-intuitive knockouts using a metabolic model for lipid production in R. toruloides. Four computationally designed mutants were obtained by the deletion of the genes involved in PGI1, GDH1, IDH and IDP1 reactions. In these strains, lipid metabolism is fully coupled to growth, with maximum productivities ranging from 26 to 62% of lipids. By analyzing the maximum yield together with the flux distribution obtained from different knockouts, it was concluded that the double knockout strategy was an interesting alternative for obtaining growth-linked lipid production with few genetic manipulations.

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